The proliferation of modern wireless communications devices, such as cell phones, smart phones, and tablet devices, has seen an attendant rise in demand for large multimedia data capabilities for large populations of user equipment (UE) or mobile stations. These multimedia data can include streaming radio, online gaming, music, and TV at the receiver device. To support this ever increasing demand for higher data rates, multiple-access networks are being deployed based on a variety of transmission techniques such as time division multiple access (TDMA), code division multiple access (CDMA), frequency division multiple access (FDMA), orthogonal frequency division multiple access (OFDMA), and single carrier FDMA (SC_FDMA). New standards for wireless networks are also being developed. Examples of these newer standards include Long Term Evolution (LTE) and LTE-Advanced (LTE-A) being developed by the third generation partnership project (3GPP), the 802.11 and 802.16 family of wireless broadband standards maintained by the Institute of Electric and Electronic Engineers (IEEE), WiMAX, an implementation of the IEEE 802.11 standard from the WiMAX Forum, as well as others. Networks based on these standards provide multiple-access to support multiple simultaneous users by sharing available network resources.
Wireless communication networks such as a heterogeneous network include multiple base stations to support downlink and uplink communications with multiple receiver devices, also referred to herein as user equipment (UE). Information sent from a receiver device to a base station is referred to as uplink communication (UL), and information sent from a base station to a receiver device is referred to as a downlink (DL) communication.
In the downlink of cellular wireless systems, a single transmitter sends several coded and modulated data streams—each consisting of a sequence of coded information words, or code words—to multiple user equipment receivers over a shared physical channel. The physical channel consists of a set of distinct time-frequency-space Resource Elements (RE). A resource element is the smallest useable portion of the radio spectrum consisting of one sub-carrier during one symbol period and has dimensions of frequency and time. In each RE, a complex symbol drawn from a certain set of available symbols called a constellation is transmitted.
When the transmitter is simultaneously serving multiple receiver devices, REs are typically divided in blocks, called Resource Blocks (RB). Different resource blocks are typically assigned to different receiver devices in such a way that in each RB only one receiver device is allowed to perform transmission. In this case, signals intended for different receiver devices are constrained to be mutually orthogonal in order to avoid inter-receiver device interference. The resulting orthogonal Multiple Access (MA) schemes are widely adopted in current standards. However, it is well known that increased rates (compared to orthogonal transmission) can be achieved for all multiplexed receiver devices if these receiver devices experience sufficiently different signal-to-noise ratios (SNR). In this case, a full exploitation of the multiuser channel capacity cannot be achieved by means of orthogonal MA schemes.
To obtain higher data rates, it is necessary to perform concurrent transmission to multiple receiver devices on the available REs. This can be accomplished, by employing suitably designed non-orthogonal MA (NOMA) schemes like, for example, superposition coding (SC). Alternatively, one could use other schemes not based on linear superposition coding like the overloaded multiple access (OLMA) schemes based on codeword-level multiplexing. Examples of these include Constellation Expansion Multiple Access (CEMA) and Rate-Adaptive Constellation Expansion Multiple Access (RA-CEMA).
RA-CEMA has been proposed as a solution for non-orthogonal transmission capable of achieving the same data rates as SC while featuring lower complexity and increased flexibility. FIG. 18 illustrates one example of an exemplary RA-CEMA system 20 in a LTE wireless communication system with an RA-CEMA transmitter 10 and two receiver devices 50. The “Channel coding and rate matching” block 12 receives a message of information bits bu=(bu(1), . . . , bu(Ku)) from user u and generates a vector of coded bits eu=(eu(1), . . . , eu(Eu)). The rate-adaptive code-words multiplexer 13 collects the code words e0, . . . , eU-1 and generates a vector of symbol labels l=(l(1), . . . , l(G)). After G m-bit labels l=(l(1), . . . , l(G)) have been generated by the code-words multiplexer 13, the modulator block 14 in FIG. 18 generates a sequence of G complex modulation symbols x(x(1), . . . , x(G)) drawn from the expanded constellation χEXP. Finally, the complex symbol vector x is transmitted by means of the transmitter unit 15 using G REs in the communication system 20.
In the example shown in FIG. 18, the multiplexing matrix is selected from a library 16, 54 of pre-designed matrices available at the transmitter device 10 and at the receiver devices 50, respectively. Each matrix corresponds to one out of multiple possible trade-offs between e.g. near-user rate and far-user rate. The matrix to be used for transmission is selected by the transmitter as a function of the rates, of the expanded constellation order m and of the number of REs G computed by the scheduler 11 as described above.
The RA-CEMA scheduler 11 of FIG. 18 performs receiver device selection and transmission parameter computation. The receiver device selection is performed taking into account the single-user channel quality (CQ) and service fairness criteria. However, the algorithm associated with the receiver device selection operates prior to and independently of the employed code word multiplexing scheme. Such receiver device selection and transmission parameter computation can result in lower data rates and, ultimately, in a lower throughput.
It would be advantageous to perform user selection jointly with the computation of transmission and multiplexing parameters to obtain increased throughput.
Also, RA-CEMA implementations need a specific multiplexing matrix for each number of receiver devices, receiver devices' SNR values and receiver device rates. Therefore, for each combination of number of receiver devices, receiver device rates and set of SNR values, a specific multiplexing matrix must be designed ad-hoc. Clearly, in systems of practical interest, the number of designed matrices is very large. As a result, the size of the data structure used to store such multiplexing matrices (also referred to as Multiplexing Matrix Library) may become very large. Since all the designed matrices must be made available at the transmitter 10 and the receivers 50 as is illustrated in FIG. 18, the large size of the library results in a large memory footprint both for the transmitter 10 and receivers 50. A correspondingly large signaling overhead is required to indicate to receivers 50 which matrix has been selected from the library for transmission in each transmission time interval (TTI). It would be advantageous to provide a general multiplexing matrix design for an arbitrary number of receiver devices characterized by arbitrary SNR values and arbitrary rates that reduces the size of the required data structures and signaling overhead.
Another drawback of RA-CEMA implementations is that modulation and coding scheme (MCS) parameter computation and MCS optimization are performed sequentially. The MCS parameters are computed independently for each selected receiver device without taking into account any scheduling metric. This approach does not allow exploitation of the full potential of non-orthogonal transmission. It would be advantageous to provide a scheme in which MCS parameter computation and MCS optimization are performed jointly by taking into account in this computation also the scheduling strategy.
Thus, there is a need for improved methods and apparatus for concurrent transmission of downlink data streams in wireless communication networks.